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Linear regression and classification techniques are very common in statistical data analysis but they are often able to extract from data only linear models, which can be a limitation in real data context. Aim of this study is to build an innovative procedure to overcome this defect. Initially, a multiple linear regression analysis using the best-subset algorithm was performed to determine the variables...
Emergency physicians in small primary care hospitals seeing patients with acute neurological symptoms have difficulty differentiating ischemic from hemorrhagic strokes and from stroke mimics. Telestroke consults with experienced neurologists supplemented by computerized decision support may aid in this time critical situation. Here we present a Stroke Bayesian Network (SBN) based on a naïve Bayesian...
This paper reports the investigations and experimental procedures conducted for designing an automatic sleep classification tool basedconly in the features extracted with wavelets from EEG, EMG and EOG (electro encephalo-mio- and oculo-gram) signals, without any visual aid or context-based evaluation. Real data collected from infants was processed and classified by several traditional and bio-inspired...
There are currently approximately 45 million people in Europe who report a long standing health problem or disability; according to the World Health Organization data the total number of persons chronically ill are 860 million at a worldwide level. Within a person centric health management framework, the modern healthcare systems must move away from the 'health care' to 'health management' in order...
Increasing use of computerized systems in our daily lives creates new adversarial opportunities for which complex mechanisms are exploited to mend the rapid development of new attacks. Behavioral Biometrics appear as one of the promising response to these attacks. But it is a relatively new research area, specific frameworks for evaluation and development of behavioral biometrics solutions could not...
This paper deals with the problem of multi-agent learning of a population of players, engaged in a repeated normal-form game. Assuming boundedly-rational agents, we propose a model of social learning based on trial and error, called “social reinforcement learning”. This extension of well-known Q-learning algorithm, allows players within a population to communicate and share their experiences with...
In BCI research community, support vector machine (SVM) is an effective method for motor imagery (MI)-based electroencephalographic (EEG) classification. However, the computation of decision function during SVM classification stage for a new EEG trial is time-consuming due to the large number of support vectors (SV). This paper proposes a new method to reduce the number of support vectors so that...
Combining pattern recognition is the promising direction in designing an effective classifier systems. There are several approaches of collective decision-making, among them voting methods, where the decision is a combination of individual classifiers' outputs are quite popular. This article focuses on the problem of fuser design which uses continuous outputs of individual classifiers to make a decision...
Paper deals with the problem of designing efficient classifiers for a special case of incremental concept drift. We focus on its classification based on the multiple classifier system. For the problem under consideration we propose four simple methods of combining classification and evaluate them via computer experiments.
This paper introduces a hand tracking system in unconstrained environment. The system consists of two main stages which are initialization and tracking. In initialization, hand region is first detected by combining motion and skin color pixels. A region of interest (ROI) is then created around the detected hand region. In tracking stage, skin and motion pixels are scanned around top, left and right...
In the past few years, online social data visualization has emerged as a new platform for users to construct, share, and comment on data visualizations online. The most well known online data visualization tools include Many Eyes, Swivel, and Tableau Public. In this paper, we report our analysis of Many Eyes - an IBM research project. By analyzing all the data visualizations constructed by users from...
This paper deals with a support tool for an automation of simulation of Coloured Petri nets and selected simulation experiments conducted with the aid of the tool. The tool is called CPN Assistant, it has been developed at the home institution of the authors and cooperates with the CPN Tools software. It allows to run and manage multiple customized simulations in a network environment. The experiments...
Control of interior permanent magnet (IPMSM) is difficult because its nonlinearity and parameter uncertainty. In this paper, a fuzzy c-regression models clustering algorithm which is based on T-S fuzzy is used to model IPMSM with a series linear model and weight them by memberships. Lagrangian of constrained function is built for calculating clustering centers where training output data are considered...
Linearization of T-S fuzzy model is difficult to be achieved by using existing linearization methods because fuzzy rules and membership functions are included in T-S fuzzy models. In this paper, a new linearization method is proposed for discrete time T-S fuzzy system based on the properties of T-S fuzzy theorem. The local linear models of a T-S fuzzy model are transformed to a controllable canonical...
In this paper, a T-S fuzzy modeling and tracking control method is proposed for wheeled mobile robots by using T-S fuzzy linearization approach. The proposed method has advantages in that the linear control theories can be used for the tracking control of wheeled mobile robots after linearization of them. The local linear models are converted into controllable canonical forms respectively and then...
Autonomous steering control is the principal task in the development of an intelligent transportation system. This research paper proposes a novel approach for vision based intelligent control of unmanned vehicles. The paper addresses the problems of accurate and efficient intelligent vehicle control by incorporating a well known evolutionary algorithm cAnt-Miner. The uniqueness of the proposed algorithm...
According to some biological observations, generating output variability is one of the characteristics expected from a memory model. In this paper a BAM inspired chaotic model is used to mimic this functionality of the brain. Chaos gives the potential to create deterministic variability and control its degree of uncertainty. Using some time series generated by the trained network, largest lyapunov...
In this paper an off-grid hybrid energy system consisting of a reverse osmosis desalination plant for brackish water powered by renewable energy sources, and a diesel generator as back-up will be described. The whole system serves as a prototype for testing new automatic control methods to increase the plant reliability, which is crucial in remote arid areas. The necessary steps for the design of...
The active magnetic bearing (AMB) presents a solution for all the technical problems of the classical bearing since it ensures the total levitation of a body in space eliminating any mechanical contact between the rotor and the stator. The goal of our work is to show the control efficiency of a magnetic sustention, characterized by its nonlinear model, using neural networks (NN). In this paper a study...
The paper deals with using so called singularity exponent in a classifier that is based on ordered distances of patterns to a given (classified) pattern. The approximation of probability distribution mapping function of the distribution of points from the viewpoint of distances from a given point in a form of a suitable power (exponent) of a distance is presented together with a way how to state it...
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